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Amethasone TREATS Rheumatoid Arthritis, the object, Rheumatoid Arthritis, is of type Disease or Syndrome, so the predication would not Celecoxib be selected because neither subject nor object is of an included semantic type. After applying this limitation, 18,085 unique predications remained.Network of predicationsNetwork filtering: degree centralityThe first cutoff applied was degree centrality. After attempting several thresholds, a node degree cutoff of 0.0000800641 was empirically chosen to provide a network with more than 50 and fewer than 100 nodes, thereby providing a humanly readable graph. This degree correlates to a node having edges connecting to 50 other nodes. For example, the concept Traumatic Brain Injury is connected to 295 other nodes with a degree of 0.0004724 and, therefore, is maintained in the network after degree filtering. However, the concept cyclooxygenase 2 is connected to only 43 concepts with a degree of 0.00006886 and so is eliminated. The 20 most highly connected concepts are shown in Figure 3, and 20 examples PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/15501003 of the 2688 nodes which had only a single connection are provided in Figure 4.Network filtering: frequency of occurrenceThese 18,085 predications extracted from neurological injury MEDLINE citations and containing a potential biomarker as subject or object were then linked together as a network. This network represents all of the known substance activity involved in neurotrauma, as indicated by the semantic predications included in SemMedDB. The nodes of the network represent arguments (subject or object) from the predications, and the edges represent the predicates or relationships between subjects and objects. Each subject-object pair might have multiple predicates. For example, both Melatonin INHIBITS Free Radicals and Melatonin COEXISTS_WITH Free Radicals may have been asserted in the literature. When counting edges in the network, each predicate between the same subject and object in such predications was counted separately. Additionally, each subject-predicate-object triplet could have been asserted once in MEDLINE (and thus in SemMedDB) or as many as dozens of times. When taking into account each predication extracted from multiple citations, the network has 6246 total nodes and 18,085 total edges. When only unique (different) predications are considered (regardless of the number citations they were extracted from), the number of nodes in the network remains 6246, but the number of edges is 14,085. This is still a rather large network; to reduce it to more manageable size, further filtering was carried out.Frequency of occurrence was used in conjunction with degree centrality to increase the saliency of the network. A given edge (predicate) between highly connected nodes (arguments) was required to have a frequency of occurrence of 2 in an attempt to eliminate spurious extractions while still including rare statements. As an example, the predication Interleukin-3 DISRUPTS Cell Death is maintained in the final network because it occurs twice in the SemMedDB predication set. Because NADPH Dehydrogenase INTERACTS_WITH Glial Fibrillary Acidic Protein occurs only a single time, it is not included in the final network. The most frequently occurring predications from this set are provided in Figure 5. This refinement requiring a frequency greater than or equal to 2 and a node degree greater than or equal to 0.0000800641 (50 or more connections) resulted in 1021 predications with 49 unique concepts (see Figure 6.

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